1. Field of Description
The present disclosure relates, in general, to computer-implemented methods for running content intelligence algorithms or software modules on digital media assets such as video images, and, more particularly, to improved methods and systems for combining content intelligence modules and output/results of such content intelligence modules for more effective use by applications.
2. Relevant Background
Recently, there have been many advances in software algorithms or modules that are useful in analyzing digital media to provide information about the media. For example, a digital asset, such as a frame of a video source or a digital image, may be analyzed with a computer application to automatically determine whether the asset includes a human face. If so, another application or module may act to determine whether the face belongs to a specific person, which may have numerous uses such as searching for images of a particular person in large asset sets such as video or image databases accessible via the Internet or to determine from surveillance cameras whether a suspected criminal has been in proximity of a particular camera location. Other algorithms or software modules may be used to provide other information such as facial expression, activity in a frame or image, a shot in a video, a brightness level of an image, and/or other specific information for a media asset. This collection of algorithms or modules may be labeled content intelligence modules or algorithms.
In general, each content intelligence algorithm is created to perform a particular task or function with relation to a media asset. Each content intelligence algorithm such as a face identifier algorithm for use with still images may output a set of result or output data. Unfortunately, most content intelligence algorithms do not return data that can be used directly as a feature or the like. Instead, the content intelligence data or results have to be post-processed to be useful, and often the post-processing further requires that the data from differing algorithms be combined to be used, e.g., brightness levels on their own may not be useful, activity identified in an image may not be useful without further data, and so on. Another reason that the content intelligence results often have to be post-processed and combined is that each content intelligence algorithm provides its output in the context of their specific environment. It is left up to another application or another content intelligence module to determine that context to properly use the results, which may make it difficult to properly combine or build upon the results of another content intelligence algorithm.